1. Technical Field
The present invention relates to an orthotope sphere decoding method for signal reconstruction in a multiple antenna system and an apparatus for the same. More particularly, the present invention relates to an orthotope sphere decoding method for signal reconstruction in a multiple antenna system and an apparatus for the same, in which a tree search is performed in the multiple antenna system using a depth-first method to detect a transmission symbol having a smallest PED value as an optimum signal by performing an OC-test on the nodes on which the tree search of orthotope sphere decoding will be performed and performing an SC-test on nodes passing the OC-test, thereby reducing complexity of decoding for signal reconstruction.
2. Description of the Related Art
As high-quality and high-speed data transmission is required in a wireless communication environment, a multiple-input and multiple-output (hereinafter, referred to as ‘MIMO’) system using multiple antennas is used for efficient use of limited frequencies. The MIMO system can be operated according to a space-time coding scheme or a space-division multiplexing scheme. The space-time coding scheme is a technique capable of enhancing reliability of a wireless communication system by encoding data transmitted from different antennas. The space-division multiplexing scheme is a technique which increases data transmission rates by simultaneously transmitting data independent from one another through multiple antennas.
Various techniques have been proposed to detect transmission symbols from received symbols at a receiving end when the MIMO system transmits independent symbols through multiple transmission antennas in the space-division multiplexing scheme. The maximum likelihood (ML) detection technique calculates and compares Euclidean distances for all transmittable symbol vectors in order to detect the symbols.
The ML detection technique searches for transmission symbols having a shortest Euclidean distance from a received signal for all combinations of transmittable transmission symbols. However, if the number of antennas and the scale of a modulation scheme increase, complexity of ML detection is exponentially increased, and thus it is very difficult to implement ML detection. In order to reduce the complexity of ML detection, a sphere decoding technique has been developed.
Since the sphere decoding technique calculates Euclidean distance only for a set of symbol vectors existing in a sphere having a radius that is set in an initial stage considering noise variance and channel state, it can reduce the complexity of ML detection. However, complexity of a sphere decoder varies depending upon initial radius and a method of searching for lattice vectors existing in a sphere. That is, if the initial radius is set too large, numerous lattice vectors may exist within the initial radius, and thus the sphere decoder will have a complexity almost equal to that of an ML detector. In addition, if the initial radius is too small, the sphere decoder is unable to search for an effective lattice vector. In addition, if SNR of the sphere decoder is low, the number of visiting nodes, i.e., complexity, abruptly increases when tree search is performed, and thus decoding efficiency is degraded.